Database Paper Browser

Back to papers

Optimization Strategies for A/B Testing on HADOOP

Summary: Resource-aware optimization for concurrent Hive/MapReduce on Hadoop; data-dependency inter-query optimization and cluster-load modeling. First to optimize A/B testing on Hadoop; 233% speedup for concurrent vs sequential; up to 40% extra with resource tuning. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10758
Venue
VLDB
Year
2013
Pagerank
4.1945683e-05
Overall Rank
12,101 | 15.82%
DOI
-

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
588 Practical Skew Handling in Parallel Joins 1992 VLDB 0.00019604754
868 Profiling, What-if Analysis, and Cost-based Optimization of MapReduce Programs 2011 VLDB 0.00015789681
1,071 Starfish: A Self-tuning System for Big Data Analytics 2011 CIDR 0.00014312777
3,601 Large-Scale Machine Learning at Twitter 2012 SIGMOD 6.9315087e-05
Previous Page 1 / 1 Next

Semantically Similar Papers